Senior Content Engineer

Flexera Software; Bengaluru; Presencial; INR 2.000.000 - 3.500.000; Jornada completa

Descripción de la vacante

Flexera Software in Bengaluru is seeking a Senior Content Data Engineer to join our Content Operations team. You will maintain, analyze, and improve the quality of technology product data, with emphasis on data quality, dashboards, and automation.

The role blends data analysis, Power BI reporting, AI-driven process improvement, and collaboration with Engineering, Product Management, and Operations to deliver actionable insights and scalable data solutions.

Formación

• Bachelor's degree in CS/IT/Data Analytics or related field.
• 2-5 years in data analysis, data quality, or content operations.
• Strong analytical and problem-solving with large datasets.
• Proficiency in Excel and Power BI.
• SQL and Python skills for data analysis.
• Understanding of data quality concepts and validation.
• Attention to detail and data accuracy.
• Good communication and stakeholder management.
• Familiarity with AI/ML concepts in data analysis.

Responsabilidades

• Design, develop, and maintain Power BI dashboards and reports for content quality and operational metrics.
• Build KPIs and visualizations to monitor data quality and health.
• Analyze data from multiple sources and create actionable dashboards.
• Develop automated reporting to reduce manual effort.
• Improve dashboards based on requirements and feedback.
• Use Power BI to identify trends and bottlenecks.
• Leverage AI, ML, and automation to improve content operations and data quality.
• Explore AI-driven solutions for data classification, normalization, anomaly detection, and validation.
• Identify inconsistent mappings, missing content, duplicates, and data-quality issues.
• Review product lifecycle data for accuracy and completeness.

Conocimientos

Analytical Thinking

Data Quality Mindset

Problem Solving

Domain Expertise

Ownership

Collaboration

Continuous Improvement

Attention to Detail

Communication & Stakeholder Management

Educación

Bachelor's degree in Computer Science, Information Technology, Data Analytics, Engineering, or a related field

Herramientas

Power BI

Excel

SQL

Python

Descripción del empleo

Job Summary

We are looking for a Senior Content Data Engineer to join our Content Operations team and play a key role in maintaining, analyzing, and improving the quality of technology product data.

The role combines data analysis, content quality, Power BI reporting, AI-driven process improvement, and technology domain expertise. The analyst will work with large and complex datasets to identify data gaps and inconsistencies, support normalization and catalog curation, build meaningful insights through dashboards, and identify opportunities to use AI and automation to improve operational efficiency and data quality.

The ideal candidate should have strong analytical and problem-solving skills, experience with data visualization and reporting, curiosity about AI and automation, and the ability to work closely with Engineering, Product Management, and Operations teams.

Key Responsibilities

• Design, develop, and maintain Power BI dashboards and reports to provide visibility into content quality, operational performance, backlog, SLA, automation coverage, and data trends.
• Build meaningful KPIs and visualizations to help stakeholders monitor data quality and operational health.
• Analyze data from multiple sources and create dashboards that provide actionable insights to Operations, Product, and Engineering teams.
• Develop automated reporting solutions to reduce manual reporting effort.
• Continuously improve existing dashboards based on business requirements and stakeholder feedback.
• Use Power BI to identify trends, bottlenecks, quality patterns, and opportunities for process improvement.
• Identify opportunities to leverage AI, machine learning, and intelligent automation to improve content operations and data quality.
• Explore and implement AI-driven solutions for data classification, normalization, mapping recommendations, anomaly detection, and quality validation.
• Develop and evaluate AI-assisted approaches for identifying inconsistent mappings, missing content, duplicate products, and potential data-quality issues.
• Analyze large datasets to identify data gaps, inconsistencies, anomalies, duplicates, and quality issues.
• Perform and support data normalization, mapping, classification, enrichment, and validation.
• Review technology product, manufacturer, version, release, and lifecycle data to ensure accuracy, completeness, and consistency.

Required Skills & Qualifications

• Bachelors degree in Computer Science, Information Technology, Data Analytics, Engineering, or a related field.
• 2-5 years of experience in data analysis, data quality, content operations, data management, or a related role.
• Strong analytical and problem-solving skills with experience working with large datasets.
• Strong proficiency in Excel and Power BI.
• Working knowledge of SQL, python for data analysis and investigation.
• Understanding of data quality, normalization, mapping, classification, and validation concepts.
• Strong attention to detail and commitment to data accuracy.
• Good understanding of data visualization and KPI development.
• Basic understanding of AI/ML concepts and their application in data analysis and automation.
• Strong communication and stakeholder-management skills.
• Ability to manage multiple priorities and work effectively in a fast-paced environment.

Good to Have

• Experience working with IT asset management (ITAM), technology/product catalogs, CMDB, or IT service management (ITSM) data.
• Experience with Power BI or other data visualization and reporting tools.
• Experience with Python or other scripting languages for data analysis and automation.
• Knowledge of APIs, data pipelines, web crawlers, or integrations.
• Familiarity with JIRA or similar ticket-management tools.
• Experience working with product lifecycle data such as GA, EOL, EOS, and obsolete products.
• Experience with data governance, data quality frameworks, or master data management.
• Exposure to AI/ML-based data automation or rule-generation solutions.

Key Competencies

• Analytical Thinking: Ability to break down complex data problems and identify root causes.
• Data Quality Mindset: Strong focus on accuracy, consistency, completeness, and reliability of data.
• Problem Solving: Ability to investigate issues and develop practical solutions.
• Domain Expertise: Ability to understand technology products and build expertise in the assigned data domain.
• Ownership: Takes responsibility for assigned work and drives issues through to resolution.
• Collaboration: Works effectively with Engineering, Product, Operations, and other stakeholders.
• Continuous Improvement: Looks for opportunities to improve processes, automation, and operational efficiency.
• Attention to Detail: Able to identify subtle inconsistencies and maintain high-quality data standards.